1. Field of the Invention
The present invention relates to an image processing method, an image processing apparatus and a semiconductor manufacturing method.
2. Background Art
In recent years, along miniaturization of semiconductor devices, surface patterns of semiconductors are also becoming finer. Therefore, in CD (critical dimension) measurement of a surface pattern, a tolerance of measurement error becomes stricter.
In order to improve precision of CD measurement, a scanning electron microscopy such as a CD-SEM (critical dimension-scanning electron microscopy or microscope) or the like is generally used. The CD-SEM irradiates an electron beam onto a sample, and detects secondary electrons from the sample. Detection quantity of secondary electrons mainly depends on a surface pattern. Therefore, a surface shape of the sample can be imaged based on the detection quantity of the secondary electrons. An image obtained based on the detection quantity of the secondary electrons is hereinafter referred to as a “secondary electron image”. The CD-SEM extracts an outline of the surface pattern from the secondary electron image, and measures dimensions of a desired part of the surface pattern.
The contrast of the secondary electron image varies depending on a surface pattern and a material of the sample. Therefore, in order to carry out a stable measurement with the CD-SEM, the contrast of the secondary electron image needs to be improved. In order to improve the contrast, a total grayscale level is calculated from a gray value of an area of interest within an image, and the contrast of the secondary electron image is converted based on the grayscale level (see Japanese Patent Application No. H11-296680 Publication).
The secondary electron image depends on not only the surface pattern of the sample but also a material of the sample, a potential of the sample, and an electric field near the sample. A contrast that depends on the surface shape of the sample is called a shape contrast. A contrast that depends on the material of the sample is called a material contrast. A contrast that depends on the potential of the sample and the electric field near the sample is called a potential contrast. In this way, the secondary electron image includes various contrasts.
A contrast that is necessary for a CD measurement is a shape contrast attributable to a surface shape. Other contrasts cause a measurement error. This measurement error is called a “SEM bias”. The SEM bias is a difference between a measurement value calculated based on a surface image obtained from above the sample with the CD-SEM or the like and an accurate measurement value calculated based on a cross-sectional image on the cut surface of the sample. When a measurement value is calculated based on a surface image of only a shape contrast, the SEM bias becomes constant. However, in general, when a space width becomes small and when the influence of the potential contrast becomes noticeable, the SEM bias at the time of measuring the space width becomes small. This is called a “SEM bias variation”.
For example, a contrast of a surface image changes depending on a space width as shown in FIG. 11. When a space width is large, gray values of a line L and space S become substantially equal, and therefore, there is little difference in the contrast of the surface image between the line L and the space S, as shown by a profile along a line A—A. On the other hand, when a space width becomes small, a gray value at the space S side becomes smaller than that at the line L side, as shown by profiles along a line B—B and a line C—C, respectively. Therefore, in this case, the surface image becomes dark at the part of the space S. This is because a distance between adjacent lines becomes small, and the electric field due to an electric charge accumulated on the lines affects the secondary electrons from the bottom surface of the space S, and this decreases the quantity of the secondary electrons detected by a detector. Because the contrast changes depending on the space width, the SEM bias varies.
If the SEM bias is constant, it is sufficient to calculate the SEM bias from a surface image and a cross-sectional image at one position of the sample. However, because the SEM bias changes as described above, the SEM bias needs to be calculated from surface images and cross-sectional images at many positions having various patterns. This calculation involves enormous amount of work and has poor work efficiency. In a complex device configuration, various contrasts are conjugated. Therefore, it is difficult to calculate the SEM bias. These problems cannot be solved by gamma correction or by a conventional technique described in Japanese Patent Application No. H11-296680 Publication.
It is, therefore, desired to obtain an image processing method and an image processing apparatus capable of correcting a variation in the SEM bias more easily than conventional practices, and capable of measuring a surface pattern of a sample accurately and efficiently.